Datensatz - opendata.hessen.de

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nach Themen

[{"children": [], "color": "MediumVioletRed", "highlighted": false, "icon": "fa fa-users", "id": "c51346dd-559a-413f-8f68-9aef3fbfd395", "name": "bevolkerung-und-gesellschaft", "package_count": 14, "title": "Bev\u00f6lkerung und Gesellschaft"}, {"children": [], "highlighted": false, "id": "b345842a-23c8-4855-bbf2-4be85039a3f7", "name": "bildung-kultur-und-sport", "title": "Bildung, Kultur und Sport"}, {"children": [], "highlighted": false, "id": "b5b42983-23a9-402f-b78c-dd0654538486", "name": "energie", "title": "Energie"}, {"children": [], "color": "Darkred", "highlighted": false, "icon": "fa fa-heartbeat", "id": "c51f7f61-5c5a-406e-b139-453878b112b7", "name": "gesundheit", "package_count": 4, "title": "Gesundheit"}, {"children": [], "highlighted": false, "id": "71d3dfc9-8f47-4926-9cff-3b19b11a2404", "name": "internationale-themen", "title": "Internationale Themen"}, {"children": [], "color": "DarkRed", "highlighted": false, "icon": "fa fa-balance-scale", "id": "e2d9e3b8-2e2c-4ab4-b2d4-867b4539157b", "name": "justiz-rechtssystem-und-offentliche-sicherheit", "package_count": 3, "title": "Justiz, Rechtssystem und \u00f6ffentliche Sicherheit"}, {"children": [], "highlighted": false, "id": "785c8121-9464-4bd2-a9ae-7b9a6990b201", "name": "landwirtschaft-fischerei-forstwirtschaft-und-nahrungsmittel", "title": "Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel"}, {"children": [], "color": "CadetBlue", "highlighted": false, "icon": "fa fa-bank", "id": "b739013c-1f67-4a6a-82d0-6b894f64e0d7", "name": "regierung-und-offentlicher-sektor", "package_count": 18, "title": "Regierung und \u00f6ffentlicher Sektor"}, {"children": [], "color": "DarkGoldenRod", "highlighted": false, "icon": "fa fa-city", "id": "2b667098-7c6a-4084-9497-fd0107aea558", "name": "regionen-und-stadte", "package_count": 1, "title": "Regionen und St\u00e4dte"}, {"children": [], "color": "DarkGreen", "highlighted": false, "icon": "fa fa-leaf", "id": "d06ae5e3-bfbc-4923-adcc-dc492f399458", "name": "umwelt", "package_count": 40, "title": "Umwelt"}, {"children": [], "color": "DimGray", "highlighted": false, "icon": "fa fa-road", "id": "224db1bd-e82e-462c-b955-a0c79986cbef", "name": "verkehr", "package_count": 3, "title": "Verkehr"}, {"children": [], "highlighted": false, "id": "c215406d-d866-4e00-b0fb-5ebacaa2d626", "name": "vorlaufige-daten", "title": "Vorl\u00e4ufige Daten"}, {"children": [], "color": "Teal", "highlighted": false, "icon": "fa fa-line-chart", "id": "54917440-dd7c-45d6-83a7-f03099534059", "name": "wirtschaft-und-finanzen", "package_count": 4, "title": "Wirtschaft und Finanzen"}, {"children": [], "color": "DarkTurquoise", "highlighted": false, "icon": "fa fa-microscope", "id": "110f547b-8ba7-4062-bef3-f920cc7d0572", "name": "wissenschaft-und-technologie", "package_count": 5, "title": "Wissenschaft und Technologie"}]

nach Schlagwörtern

[{"active": false, "count": 58, "display_name": "Berlin", "id": "86376f99-3886-49fc-92e6-6b3320a420f6", "name": "Berlin", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 58, "display_name": "Bundesl\u00e4nder", "id": "c89fa8ad-3310-4cdd-8912-207a8ab7b38a", "name": "Bundesl\u00e4nder", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 58, "display_name": "Hamburg", "id": "61f1a029-cb53-4228-880d-351021f6b0d4", "name": "Hamburg", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 33, "display_name": "Deutschland", "id": "59d12a29-faf7-4fd4-aa8a-9df52474783a", "name": "Deutschland", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 33, "display_name": "Stadtstaaten", "id": "6cba4ee8-3a9d-4256-b01d-959977986ca6", "name": "Stadtstaaten", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 33, "display_name": "Summe der L\u00e4nder", "id": "92f29afd-7d32-46ab-a7ed-6040d8ce23b1", "name": "Summe der L\u00e4nder", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 31, "display_name": "Boden", "id": "5fb13590-7897-4861-8ff5-271edcbb4441", "name": "Boden", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 30, "display_name": "Regional", "id": "e174dd36-3f03-4b1f-81c2-cb78bc1c0e9c", "name": "Regional", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 17, "display_name": "AdVMIS", "id": "84959740-44f9-4c8d-a6ea-e3eb3dd52a53", "name": "AdVMIS", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 15, "display_name": "Umwelt\u00f6konomische Gesamtrechnungen der L\u00e4nder - Energierechnungen", "id": "e016e8f7-9a49-48f7-88a4-170c6cf362c3", "name": "Umwelt\u00f6konomische Gesamtrechnungen der L\u00e4nder - Energierechnungen", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 14, "display_name": "Armutsgef\u00e4hrdungsquote", "id": "0b463c4d-2298-4501-8a95-a94565095287", "name": "Armutsgef\u00e4hrdungsquote", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 14, "display_name": "Sozialberichterstattung in der amtlichen Statistik", "id": "e7f326de-a5a1-4de8-b41f-4c23d5942e39", "name": "Sozialberichterstattung in der amtlichen Statistik", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 10, "display_name": "Umwelt\u00f6konomische Gesamtrechnungen der L\u00e4nder - Gase", "id": "d416617d-6435-4c93-bcf5-276fdfa751ed", "name": "Umwelt\u00f6konomische Gesamtrechnungen der L\u00e4nder - Gase", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 9, "display_name": "ATKIS", "id": "cad42df6-7147-4de7-b7f3-0c93c41396e1", "name": "ATKIS", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 9, "display_name": "Bodenschutz", "id": "6891d940-bdda-4065-bb5b-4a223acc127c", "name": "Bodenschutz", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 9, "display_name": "m\u00e4nnlich", "id": "2b38bf58-b5b3-4e23-aef2-e8efb0969782", "name": "m\u00e4nnlich", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 9, "display_name": "Wasser", "id": "6a90026b-2557-4a49-883c-dbba1410e015", "name": "Wasser", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 7, "display_name": "Biotop", "id": "c2639915-a123-48c1-84a2-b27ef13e1c55", "name": "Biotop", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 7, "display_name": "INSPIRE-Datenmodell", "id": "de6e3bcd-c4ab-4f61-a142-b0729e401412", "name": "INSPIRE-Datenmodell", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 7, "display_name": "INSPIRE-Thema SO", "id": "2551616e-8b8d-494b-bf66-423c57354d77", "name": "INSPIRE-Thema SO", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 6, "display_name": "CO2-Emissionen", "id": "e76f59f5-c9a3-494d-b88e-83203968f715", "name": "CO2-Emissionen", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 6, "display_name": "Gr\u00fcnland", "id": "1a622a14-a7dd-4491-8257-5aa2eed64a1f", "name": "Gr\u00fcnland", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 6, "display_name": "Wirtschaft A-T", "id": "9744cf17-b6af-4130-9667-c01c218bfa2e", "name": "Wirtschaft A-T", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "ATKIS_-Basis-DLM", "id": "db60880e-dc01-4ea7-9f3f-96f6154fb916", "name": "ATKIS_-Basis-DLM", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "DLM", "id": "ec53cd88-31be-44fe-844a-694ed9a7b341", "name": "DLM", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "Gebiete mit naturbedingten Risiken", "id": "79bc6453-68d7-402f-8eda-73bfc2fc013c", "name": "Gebiete mit naturbedingten Risiken", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "naturbedingte Risiken", "id": "990858f9-ee76-4bff-989f-ccbe1647b0df", "name": "naturbedingte Risiken", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "Prim\u00e4renergieverbrauch", "id": "62f87f7b-a9f7-4f7d-8a6c-dfda7eb9b423", "name": "Prim\u00e4renergieverbrauch", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "Prim\u00e4renergieverbrauch Index 2010_100", "id": "1728c206-09c9-4664-bcd7-c667c7f61e96", "name": "Prim\u00e4renergieverbrauch Index 2010_100", "vocabulary_id": null, "vocabulary_name": null}, {"active": false, "count": 5, "display_name": "Pr\u00e4sentationsgraphik", "id": "30e3d2d2-d7dd-4b31-bb8b-318397262653", "name": "Pr\u00e4sentationsgraphik", "vocabulary_id": null, "vocabulary_name": null}]

nach Regionen

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"", "display_name": "2005", "extras": [], "groups": [], "id": "75941662-864c-4004-ab97-a9fd6361a487", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2005", "num_followers": 0, "package_count": 68, "state": "active", "title": "2005", "type": "time"}, {"approval_status": "approved", "count": 5, "created": "2025-05-14T09:25:38.577806", "description": "", "display_name": "2006", "extras": [], "groups": [], "id": "75f65511-754f-4d5c-86c3-7e2701517b09", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2006", "num_followers": 0, "package_count": 71, "state": "active", "title": "2006", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:44.353029", "description": "", "display_name": "2007", "extras": [], "groups": [], "id": "b3937959-1bf8-4928-9c99-3c03aea50609", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2007", "num_followers": 0, "package_count": 70, "state": "active", "title": "2007", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:45.821140", "description": "", "display_name": "2008", "extras": [], "groups": [], "id": "e9ae7cb0-d931-44df-bc06-083157e61d11", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2008", "num_followers": 0, "package_count": 70, "state": "active", "title": "2008", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:51.514220", "description": "", "display_name": "2009", "extras": [], "groups": [], "id": "9e39c5b5-70c1-47a2-9628-dd3daf472043", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2009", "num_followers": 0, "package_count": 70, "state": "active", "title": "2009", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:33.692823", "description": "", "display_name": "2010", "extras": [], "groups": [], "id": "21342717-6c34-47ec-9c6b-81583a92c87e", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2010", "num_followers": 0, "package_count": 88, "state": "active", "title": "2010", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:35.305599", "description": "", "display_name": "2011", "extras": [], "groups": [], "id": "3fde46aa-e991-46a0-876f-6da4c21f2fe6", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2011", "num_followers": 0, "package_count": 113, "state": "active", "title": "2011", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:34.058200", "description": "", "display_name": "2012", "extras": [], "groups": [], "id": "14e704d2-7f56-490c-b9cd-5e755ca36320", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2012", "num_followers": 0, "package_count": 127, "state": "active", "title": "2012", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:35.575519", "description": "", "display_name": "2013", "extras": [], "groups": [], "id": "f7fddc70-d89a-4f3e-9e9d-6c917f488b70", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2013", "num_followers": 0, "package_count": 128, "state": "active", "title": "2013", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:35.821455", "description": "", "display_name": "2014", "extras": [], "groups": [], "id": "15db0e9c-4098-4524-921b-d437147c8592", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2014", "num_followers": 0, "package_count": 129, "state": "active", "title": "2014", "type": "time"}, {"approval_status": "approved", "count": 3, "created": "2025-05-14T09:25:36.245956", "description": "", "display_name": "2015", "extras": [], "groups": [], "id": "f803f07a-ae62-4296-9fbc-b3dd07420c6f", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2015", "num_followers": 0, "package_count": 138, "state": "active", "title": "2015", "type": "time"}, {"approval_status": "approved", "count": 4, "created": "2025-05-14T09:25:34.456394", "description": "", "display_name": "2016", "extras": [], "groups": [], "id": "67689b63-20a3-4e07-ac7d-82844b7e16dd", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2016", "num_followers": 0, "package_count": 148, "state": "active", "title": "2016", "type": "time"}, {"approval_status": "approved", "count": 5, "created": "2025-05-14T09:25:33.969813", "description": "", "display_name": "2017", "extras": [], "groups": [], "id": "9a3e437c-c506-4181-8eaa-97a03639e681", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2017", "num_followers": 0, "package_count": 173, "state": "active", "title": "2017", "type": "time"}, {"approval_status": "approved", "count": 4, "created": "2025-05-14T09:25:34.137682", "description": "", "display_name": "2018", "extras": [], "groups": [], "id": "e2758b9d-4474-4787-a08a-e3cd51e0b53a", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2018", "num_followers": 0, "package_count": 195, "state": "active", "title": "2018", "type": "time"}, {"approval_status": "approved", "count": 8, "created": "2025-05-14T09:25:34.217853", "description": "", "display_name": "2019", "extras": [], "groups": [], "id": "2bee7023-2ff9-4048-a9a1-a73d2289a5ec", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2019", "num_followers": 0, "package_count": 216, "state": "active", "title": "2019", "type": "time"}, {"approval_status": "approved", "count": 12, "created": "2025-05-14T09:25:33.777389", "description": "", "display_name": "2020", "extras": [], "groups": [], "id": "0a75521c-0caa-43cd-9eee-708db30048b3", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2020", "num_followers": 0, "package_count": 230, "state": 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"approved", "count": 16, "created": "2025-05-14T09:25:50.551972", "description": "", "display_name": "2026", "extras": [], "groups": [], "id": "9674f04e-e4f4-44b1-88e5-2f8e98690a0e", "image_display_url": "", "image_url": "", "is_organization": false, "name": "2026", "num_followers": 0, "package_count": 70, "state": "active", "title": "2026", "type": "time"}]

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Räumliche Verteilung auf einen Blick

Die Karte zeigt, wie sich die aktuell gefundenen Datensätze über Hessen verteilen: je dunkler ein Gebiet, umso mehr Datensätze liegen dort vor. Dabei überlagern sich Landkreise (rot) mit Städten und Gemeinden (blau).

Datensätze, die ganze Regierungsbezirke oder ganz Hessen umfassen (auch dann, wenn sich die darin enthaltenen Daten selbst bis auf Gemeindeebene aufgliedern), werden hier weggelassen, weil ihre Anzahl keine regionalen Unterschiede ausmachen.

Mit einem Klick auf eine Region fügen sie diese dem Datensatz-Filter hinzu. Zugleich wird damit die darunterliegende Ebene aufgedeckt, d.h. ein Klick auf einen Landkreis zeigt seine Gemeinden.

Tipps und Tricks

Kreisfreie Städte werden wie Städte und Gemeinden behandelt. Sie erscheinen in blau, auf der Ebene der Landkreise (rot) sind ihre Flächen leer.
Mehrere Filter sind UND-verknüpft. Wenn Sie etwa Darmstadt und Kassel als Filter hinzufügen, dann suchen Sie nach Datensätzen, die Daten sowohl über Darmstadt als auch über Kassel enthalten (also nicht nach solchen, die entweder nur Darmstadt oder nur Kassel enthalten).
Die Filter von Landkreisen und Gemeinden wirken getrennt. Wenn Sie also nach einem Landkreis filtern, sind nicht automatisch die Datensätze aller kreisangehörigen Gemeinden gleich mit enthalten.
Wenn sie nur nach einer Gemeinde filtern wollen, dann klicken sie zunächst auf ihren Landkreis - und haben ihn dadurch sogleich als Filter hinzugefügt. Klicken Sie dann erst auf die Gemeinde und aktivieren Sie sie somit ebenfalls als Filter; danach entfernen Sie wieder den Landkreis in der Reihe der aktiven Filter durch Klick auf das x.
Diese Karte dient nur der schnellen Orientierung. Wenn Sie Datensätze gezielt über Regionen und Verwaltungsebenen suchen, dann wechseln Sie zum Dashboard "Regionen". Dort können Sie auch alle Ebenen einzeln ein- und ausblenden und sehen eine Legende über die zahlenmäßige Verteilung.
Region ist nicht identisch mit Herausgeber. Daten über eine Gemeinde können, müssen aber nicht von dieser Gebietskörperschaft stammen, sondern ebenso gut von einer ganz anderen Behörde.
Die Anzahl der Datensätze sagt noch nichts aus über die Menge an Daten, die darin enthalten ist. So kann z.B. ein WMS-Dienst aus lediglich einem Layer bestehen oder aber zahlreiche Layer enthalten zu ganz unterschiedlichen Aspekten.

HVD Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

Kilometrierung

Kilometrierungspunkte der hessischen Gewässer, berechnet auf der Basis von Routen für Gewaessernetz_DLM25, als Distanz ab den Mündungspunkten. Dabei befindet sich bei Gewässern...
- WMS
- WFS
- REST
- ATOM
Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

Hessen_2022_Laerm_EU_Industrie_IED_Anlagen_LDEN

EU-Umgebungslärmrichtlinie 2002/49/EG - Lärmkartierung 2022: Industrielärm in Hessen (Ballungsräume Darmstadt, Frankfurt, Hanau, Kassel, Offenbach, Wiesbaden) - IED-Anlagen...
- WMS
Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

Hessen_2022_Laerm_EU_Grossflughafen_LDEN

EU-Umgebungslärmrichtlinie 2002/49/EG - Lärmkartierung 2022: Großflughafen in Hessen (Frankfurt am Main) - Fluglärm nach BUF (Berechnungsmethode für den Umgebungslärm von...
- WMS
Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

Hessen_2022_Laerm_EU_Industrie_IED_Anlagen_LNight

EU-Umgebungslärmrichtlinie 2002/49/EG - Lärmkartierung 2022: Industrielärm in Hessen (Ballungsräume Darmstadt, Frankfurt, Hanau, Kassel, Offenbach, Wiesbaden) - IED-Anlagen...
- WMS
HVD Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

INSPIRE HE SO BFD50 - SO.YieldPotential M191 - Download EPSG 3044 (25832)

INSPIRE HE SO BFD50 - Bodenflächendaten 1:50 000 für Hessen (BFD50, 2. Ausbaustufe, Schema Soil, DE7, DE-HE) - SO.YieldPotential M191 Ertragspotenzial - Download EPSG 3044 (x/y...
- WMS
HVD Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

INSPIRE HE SO BFD50 - SO.FieldCapacity1mTXT M177 - Download EPSG 3044 (25832)

INSPIRE HE SO BFD50 - Bodenflächendaten 1:50 000 für Hessen (BFD50, 2. Ausbaustufe, Schema Soil, DE7, DE-HE) - SO.FieldCapacity1mTXT M177 Feldkapazität im 1. Meter - Download...
- WMS
Datensatz · Hessisches Landesamt für Naturschutz, Umwelt und Geologie

Hessen_2022_Laerm_EU_Grossflughafen_LNight

EU-Umgebungslärmrichtlinie 2002/49/EG - Lärmkartierung 2022: Großflughafen in Hessen (Frankfurt am Main) - Fluglärm nach BUF (Berechnungsmethode für den Umgebungslärm von...
- WMS
Datensatz · ÖbVI

Standorte der ÖbVi Hessen

Standorte aller öffentlich bestellten Vermessungsingenieure in Hessen.
- WMS
- WFS
- REST
- ATOM
Datensatz · Hessisches Statistisches Landesamt

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000...

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000 Einwohner/-innen, Geschlecht sowieLänderanteil am Gesundheitspersonal in Deutschland - Jahr...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000...

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000 Einwohner/-innen, Länderanteil amGesundheitspersonal in Deutschland sowie nach Art derEinrichtung...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000...

Gesundheitspersonalrechnung der Länder: Gesundheitspersonalam 31.12. je 1000 Einwohner/-innen, Anteil an der jeweiligenEinrichtungsart, Geschlecht sowie nach Art der...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Gesundheitspersonalrechnung der Länder: Vollzeitäquivalente(VZÄ) im...

Gesundheitspersonalrechnung der Länder: Vollzeitäquivalente(VZÄ) im Gesundheitswesen am 31.12., je 100 Beschäftigtenach Art der Einrichtung (14) - Jahr - regionale...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Bruttowertschöpfung (in jew. Preisen) und Erwerbstätige inder...

Bruttowertschöpfung (in jew. Preisen) und Erwerbstätige inder Gesundheitswirtschaft - Jahr - regionale Tiefe:Bundesländer
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Bruttowertschöpfung in der Gesundheitswirtschaft, jeEinwohner/-in sowie...

Bruttowertschöpfung in der Gesundheitswirtschaft, jeEinwohner/-in sowie Länderanteil an der Bruttowertschöpfungder Gesundheitswirtschaft in Deutschland - Jahr - regionaleTiefe:...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Erwerbstätige in der Gesundheitswirtschaft, je 1000Einwohner/-innen sowie...

Erwerbstätige in der Gesundheitswirtschaft, je 1000Einwohner/-innen sowie Länderanteil an den Erwerbstätigender Gesundheitwirtschaft in Deutschland - Jahr - regionaleTiefe:...
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Armutsgefährdungsquote nach Geschlecht in Deutschland - Jahr- regionale...

Armutsgefährdungsquote nach Geschlecht in Deutschland - Jahr- regionale Tiefe: Bundesländer (ab 2020)
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Armutsgefährdungsquote nach Geschlecht und Altersgruppen (5)(Bundesmedian) -...

Armutsgefährdungsquote nach Geschlecht und Altersgruppen (5)(Bundesmedian) - Jahr - regionale Tiefe: Bundesländer (ab2020)
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Armutsgefährdungsquote nach Geschlecht und Altersgruppen (5)(Landesmedian) -...

Armutsgefährdungsquote nach Geschlecht und Altersgruppen (5)(Landesmedian) - Jahr - regionale Tiefe: Bundesländer (ab2020)
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Armutsgefährdungsquote nach Staatsangehörigkeit undMigrationshintergrund -...

Armutsgefährdungsquote nach Staatsangehörigkeit undMigrationshintergrund - Jahr - regionale Tiefe:Bundesländer (ab 2020)
- TXT
- CSV
- REST
Datensatz · Hessisches Statistisches Landesamt

Armutsgefährdungsquote nach Erwerbsstatus (5) - Jahr -regionaleTiefe:...

Armutsgefährdungsquote nach Erwerbsstatus (5) - Jahr -regionaleTiefe: Bundesländer (ab 2020)
- TXT
- CSV
- REST

Sie können dieses Register auch über die API (siehe API-Dokumentation) abrufen.

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